Identification of Immune-Related Prognostic Biomarkers Based on the Tumor Microenvironment in 20 Malignant Tumor Types With Poor Prognosis

Construction and optimization of multi-platform precision pathways for precision medicine

In the enduring challenge against disease, advancements in medical technology have empowered clinicians with novel diagnostic platforms. Whilst in some cases, a single test may provide a confident diagnosis, often additional tests are required. However, to strike a balance between diagnostic accuracy and cost-effectiveness, one must rigorously construct the clinical pathways. Here, we developed a framework to build multi-platform precision pathways in an automated, unbiased way, recommending the key steps a clinician would take to reach a diagnosis. We achieve this by developing a confidence score, used to simulate a clinical scenario, where at each stage, either a confident diagnosis is made, or another test is performed. Our framework provides a range of tools to interpret, visualize and compare the pathways, improving communication and enabling their evaluation on accuracy and cost, specific to different contexts. This framework will guide the development of novel diagnostic pathways for different diseases, accelerating the implementation of precision medicine into clinical practice.

Immune and stromal transcriptional patterns that influence the outcome of classic Hodgkin lymphoma

Classic Hodgkin lymphoma (cHL) is characterized by a rich immune microenvironment as the main tumor component. It involves a broad range of cell populations, which are largely unexplored, even though they are known to be essential for growth and survival of Hodgkin and Reed-Sternberg cells. We profiled the gene expression of 25 FFPE cHL samples using NanoString technology and resolved their microenvironment compositions using cell-deconvolution tools, thereby generating patient-specific signatures. The results confirm individual immune fingerprints and recognize multiple clusters enriched in refractory patients, highlighting the relevance of: (1) the composition of immune cells and their functional status, including myeloid cell populations (M1-like, M2-like, plasmacytoid dendritic cells, myeloid-derived suppressor cells, etc.), CD4-positive T cells (exhausted, regulatory, Th17, etc.), cytotoxic CD8 T and natural killer cells; (2) the balance between inflammatory signatures (such as IL6, TNF, IFN-γ/TGF-β) and MHC-I/MHC-II molecules; and (3) several cells, pathways and genes related to the stroma and extracellular matrix remodeling. A validation model combining relevant immune and stromal signatures identifies patients with unfavorable outcomes, producing the same results in an independent cHL series. Our results reveal the heterogeneity of immune responses among patients, confirm previous findings, and identify new functional phenotypes of prognostic and predictive utility.

The prognostic value of a combined immune score in tumor and immune cells assessed by immunohistochemistry in triple-negative breast cancer

BACKGROUND

This study aimed to develop a novel combined immune score (CIS)-based model assessing prognosis in triple-negative breast cancer (TNBC).

METHODS

The expression of eight immune markers (PD-1, PD-L1, PD-L2, IDO, TIM3, OX40, OX40L, and H7-H2) was assessed with immunohistochemistry on the tumor cells (TCs) and immune cells (ICs) of 227 TNBC cases, respectively, and subsequently associated with selected clinicopathological parameters and survival. Data retrieved from The Cancer Genome Atlas (TCGA) were further examined to validate our findings.

RESULTS

All immune markers were often expressed in TCs and ICs, except for PD-1 which was not expressed in TCs. In ICs, the expression of all immune markers was positively correlated between one another, except between PD-L1 and OX40, also TIM3 and OX40. In ICs, PD-1, PD-L1, and OX40L positive expression was associated with a longer progression-free survival (PFS; p = 0.040, p = 0.020, and p = 0.020, respectively). In TCs, OX40 positive expression was associated with a shorter PFS (p = 0.025). Subsequently, the TNBC patients were classified into high and low combined immune score groups (CIS-H and CIS-L), based on the expression levels of a selection of biomarkers in TCs (TCIS-H or TCIS-L) and ICs (ICIS-H or ICIS-L). The TCIS-H group was significantly associated with a longer PFS (p < 0.001). Furthermore, the ICIS-H group was additionally associated with a longer PFS (p < 0.001) and overall survival (OS; p = 0.001), at significant levels. In the multivariate analysis, both TCIS-H and ICIS-H groups were identified as independent predictors of favorable PFS (p = 0.012 and p = 0.001, respectively). ICIS-H was also shown to be an independent predictor of favorable OS (p = 0.003). The analysis of the mRNA expression data from TCGA also validated our findings regarding TNBC.

CONCLUSION

Our novel TCIS and ICIS exhibited a significant prognostic value in TNBC. Additional research would be needed to strengthen our findings and identify the most efficient prognostic and predictive biomarkers for TNBC patients.

Integrated Analysis of C16orf54 as a Potential Prognostic, Diagnostic, and Immune Marker across Pan-Cancer

Chromosome 16 open reading frame 54 (C16orf54) is a protein coding gene, showing a biased expression in the bone marrow, lymph node, and 11 other tissues. Reports on the function of C16orf54 in the onset and development of tumours remain scarce. Clinical information and tumour expression profile data from The Cancer Genome Atlas (TCGA), Cancer Cell Line Encyclopedia (CCLE), and Genotype-Tissue Expression (GTEx) were utilized to determine the relationship between C16orf54 expression and prognosis, diagnosis, immune microenvironment, heterogeneity, and stemness across pan-cancer. The findings ascertained that C16orf54 was expressed at a low level in most cancers. Furthermore, C16orf54 could distinguish between cancer and normal tissues with high accuracy in most cancers, and the prognostic significance of low C16orf54 mRNA levels differs across cancers. C16orf54 expression was positively linked to the stromal, immune, and ESTIMATE scores. On the other hand, C16orf54 was reported to be negatively correlated with tumour purity in most cancers. Further, C16orf54 expression was positively correlated with immune cell infiltration and the expression of immune regulatory genes, including chemokines, receptors, major histocompatibility complexes, immune inhibitory, and immune stimulatory genes, in most cancers. Additionally, C16orf54 expression was significantly associated with tumour heterogeneity indicators, such as tumour mutation burden (TMB) and microsatellite instability (MSI), and was significantly correlated with DNAss and RNAss tumour stemness indicators. Moreover, Kyoto Encyclopaedia of Genes and Genomes (KEGG) analysis, as well as Gene Set Enrichment analysis (GSEA), revealed that C16orf54 expression was closely linked to the signalling pathways of immune cells and factors. The integrated analysis of C16orf54 indicates it as a potential prognostic, diagnostic, and immune marker, which could be adopted as a novel target for adjuvant immunotherapy across pan-cancer.

Toxicological effects of polystyrene nanoplastics and perfluorooctanoic acid to Gambusia affinis

Plastic pollution has attracted huge attention from public and scientific community in recent years. In the environment, nanoplastics (NPs, <100 nm) can interact with persistent organic pollutants (POPs) such as perfluorooctanoic acid (PFOA) and may exacerbate associated toxic impacts. The present study aims to explore the single and combined ecotoxicological effects of PFOA and polystyrene nanoplastics (PS-NPs, 80 nm) on the PI3K/AKT3 signaling pathway using a freshwater fish model Gambusia affinis. Fish were exposed individually to PS-NPs (200 μg/L) and PFOA (50, 500, 5000 μg/L) and their chemical mixtures for 96 h. Our results showed that the co-exposure significantly altered the mRNA relative expression of PI3K, AKT3, IKKβ and IL-1β, compared to corresponding single exposure and control groups, indicating that the PFOA-NP co-exposure can activate the PI3K/AKT3 signaling pathway. The bioinformatic analyses showed that AKT3 had more probes and exhibited a significantly sensitive correlation with DNA methylation, compared to other genes (PIK3CA, IKBKB, and IL1B). Further, the mRNA expressions of PIK3CA, AKT3, and IKBKB had a significant correlation with copy number variation (CNV) in human liver hepatocellular carcinoma (LIHC). And PIK3CA had the highest mutation rate among other genes of interest for LIHC. Moreover, AKT3 showed a relatively lower expression in TAM and CAF cells, compared to PIK3CA, IKBKB, and IL1B. Besides, hsa-mir-155-5p was closely correlated with AKT3, PIK3CA, IKBKB, and IL1B. In summary, these results provide evidence that NPs could enhance the carcinogenic effects of POPs on aquatic organisms and highlight possible targets of LIHC induced by PFOA-NP co-exposure.

Influencing factors of depressive symptoms in patients with malignant tumour

OBJECTIVE

To assess the influencing factors of depressive symptoms in malignant tumour patients.

METHODS

Participants were 2079 inpatients with malignant tumour (1291: depressive symptoms; 788 no depressive symptoms). Univariable and multivariable logistic regression were used to evaluate sociodemographic and clinical factors influencing depressive symptoms.

RESULTS

Risk factors were family income ≤5000 yuan (odds ratio [OR]: 4.966, 95% confidence interval [CI]: 2.938-8.395) and 5001-10,000 yuan (OR: 3.111, 95% CI: 1.840-5.260); Karnofsky Performance Status of 70 (OR: 2.783, 95% CI: 1.281-6.042) and 80 (OR: 1.834, 95% CI: 1.139-2.953); disease course ≤1 year; palliative treatment (OR: 2.288, 95% CI: 1.292-4.055); progressive disease (OR: 1.876, 95% CI: 1.284-2.739); pain (OR: 1.973, 95% CI: 1.555-2.505); cancer type: lung (OR: 3.199, 95% CI: 1.938-5.279), oesophagus (OR: 3.288, 95% CI: 1.673-6.464), cervix (OR: 1.542, 95% CI: 1.056-2.253) and partial knowledge of disease condition (OR: 2.366, 95% CI: 1.653-3.385). Return to work (OR: 0.503, 95% CI: 0.348-0.727) and physical exercise (OR: 0.437, 95% CI: 0.347-0.551) were protective against depressive symptoms.

CONCLUSIONS

Several factors affected depressive symptoms in malignant tumour patients, including income, disease type and course, palliative treatment, return to work and physical exercise.

Novel deep learning-based survival prediction for oral cancer by analyzing tumor-infiltrating lymphocyte profiles through CIBERSORT

The tumor microenvironment (TME) within mucosal neoplastic tissue in oral cancer (ORCA) is greatly influenced by tumor-infiltrating lymphocytes (TILs). Here, a clustering method was performed using CIBERSORT profiles of ORCA data that were filtered from the publicly accessible data of patients with head and neck cancer in The Cancer Genome Atlas (TCGA) using hierarchical clustering where patients were regrouped into binary risk groups based on the clustering-measuring scores and survival patterns associated with individual groups. Based on this analysis, clinically reasonable differences were identified in 16 out of 22 TIL fractions between groups. A deep neural network classifier was trained using the TIL fraction patterns. This internally validated classifier was used on another individual ORCA dataset from the International Cancer Genome Consortium data portal, and patient survival patterns were precisely predicted. Seven common differentially expressed genes between the two risk groups were obtained. This new approach confirms the importance of TILs in the TME and provides a direction for the use of a novel deep-learning approach for cancer prognosis.

Hypoxic Characteristic in the Immunosuppressive Microenvironment of Hepatocellular Carcinoma

Background: Generally, hepatocellular carcinoma (HCC) exists in an immunosuppressive microenvironment that promotes tumor evasion. Hypoxia can impact intercellular crosstalk in the tumor microenvironment. This study aimed to explore and elucidate the underlying relationship between hypoxia and immunotherapy in patients with HCC.

Methods: HCC genomic and clinicopathological datasets were obtained from The Cancer Genome Atlas (TCGA-LIHC), Gene Expression Omnibus databases (GSE14520) and International Cancer Genome Consortium (ICGC-LIRI). The TCGA-LIHC cases were divided into clusters based on single sample gene set enrichment analysis and hierarchical clustering. After identifying patients with immunosuppressive microenvironment with different hypoxic conditions, correlations between immunological characteristics and hypoxia clusters were investigated. Subsequently, a hypoxia-associated score was established by differential expression, univariable Cox regression, and lasso regression analyses. The score was verified by survival and receiver operating characteristic curve analyses. The GSE14520 cohort was used to validate the findings of immune cell infiltration and immune checkpoints expression, while the ICGC-LIRI cohort was employed to verify the hypoxia-associated score.

Results: We identified hypoxic patients with immunosuppressive HCC. This cluster exhibited higher immune cell infiltration and immune checkpoint expression in the TCGA cohort, while similar significant differences were observed in the GEO cohort. The hypoxia-associated score was composed of five genes (ephrin A3, dihydropyrimidinase like 4, solute carrier family 2 member 5, stanniocalcin 2, and lysyl oxidase). In both two cohorts, survival analysis revealed significant differences between the high-risk and low-risk groups. In addition, compared to other clinical parameters, the established score had the highest predictive performance at both 3 and 5 years in two cohorts.

Conclusion: This study provides further evidence of the link between hypoxic signals in patients and immunosuppression in HCC. Defining hypoxia-associated HCC subtypes may help reveal potential regulatory mechanisms between hypoxia and the immunosuppressive microenvironment, and our hypoxia-associated score could exhibit potential implications for future predictive models.